Hamilton Lane

ETL Data Engineer

Job description

Hamilton Lane is looking to expand their team to satisfy the needs of our growing client base. Hamilton Lane is built on collaboration, teamwork and integrity. Our employees pursue excellence and always strive to do the right thing. We invest in our employees, clients and partner relationships, as well as, in the technology and resources necessary to remain competitive, working in a competitive environment that inspires innovation.

We are seeking a talented ETL Data Engineer with strong experience in Python and Azure Synapse Analytics to join our dynamic team.

As an ETL Data Engineer, you will play a critical role in our expanding data engineering team. You will be responsible for designing, developing, and maintaining ETL data integration processes primarily using Python (PySpark), Azure Synapse Analytics Pipelines, and other Azure Synapse Analytics resources, ensuring the accuracy and availability of data for our analytical needs. You will work closely with data scientists, analysts, and other stakeholders to deliver high-quality, well-organized data for insights and decision-making.

If you are passionate about data, have a strong background in ETL processes, and are eager to work with state-of-the-art Azure data solutions, we'd love to hear from you!

Key Responsibilities

  • ETL Data Engineering: Develop and maintain ETL data engineering processes using Python (PySpark) within Azure Synapse Analytics Notebooks, and/or Azure Synapse Analytics Pipelines, to ensure efficient data extraction, transformation, and loading.
  • Data Warehousing: Apply your expertise in data warehousing, understanding star schemas, facts, and dimensions, to design and build effective data storage structures in a Massively Parallel Processing (MPP) SQL Pool.
  • Data Source Expertise: Extract data from various sources, including REST APIs, SQL database tables, and CSV files.
  • Azure Synapse Analytics Expertise: Utilize your deep knowledge of Azure Synapse Analytics to design and optimize data notebooks/pipelines for scalability and performance.
  • Data Fabric Concepts: Contribute to the implementation and understanding of other Data Fabric concepts, such as data lakes, lakehouses, delta lakes, and data cataloging, to enhance data management capabilities.
  • Data Modeling: Collaborate with data architects to create data models and schemas that align with business requirements.
  • Data Quality: Implement data quality checks and validation processes to maintain data accuracy and consistency.
  • Performance Tuning: Identify and resolve performance bottlenecks and optimize ETL data notebooks/pipelines to meet SLAs.
  • Monitoring and Troubleshooting: Monitor ETL jobs, diagnose issues, and implement solutions to ensure data pipeline reliability.
  • Documentation: Maintain comprehensive documentation of ETL data engineering processes, data flows, and data transformations.
  • Collaboration: Work closely with cross-functional teams to understand data requirements and provide support for data-related initiatives.
  • Security and Compliance: Ensure data security and compliance with data governance and privacy standards.


  • Bachelor's degree in Computer Science, Information Technology, or a related field; or appropriate work experience.
  • Proven experience in ETL data engineering with significant expertise in using Python (PySpark) to perform data extraction, transformation, and loading from REST APIs, SQL database tables, and CSV files.
  • Proficiency in using Azure Synapse Analytics resources including Notebooks, Pipelines, Linked Services, and Azure Key Vault.
  • Demonstrated ability to write complex SQL queries, optimize query performance, and work with both SparkSQL and MS SQL to effectively extract, transform, and load data.
  • Knowledge of data integration best practices and tools.
  • Experience with version control systems, such as Git (Azure DevOps).
  • Strong problem-solving and analytical skills, with a keen attention to detail.
  • Excellent communication skills, both verbal and written, with the ability to work collaboratively in a team environment.
  • Must be able to work in the United States without requiring sponsorship.
  • Must be available to work hybrid schedule in our Suburban Philadelphia office

Nice-to-Have Skills

  • Certifications related to data engineering or data science (e.g., Azure Data Engineer).
  • Knowledge of big data technologies.
  • Experience with data visualization tools (e.g., Power BI, Tableau).
  • Familiarity with machine learning and data analysis.
  • Experience with Agile Methodologies

We offer a competitive salary, annual discretionary bonus and a comprehensive benefits package which includes: Medical, Prescription, Dental, Paid Time Off, 401k plan, Life and Disability Insurances, Tuition Reimbursement, Employee Stock Purchase Program, Health Club Reimbursement and Flexible Spending Accounts.

Hamilton Lane is an affirmative action-equal opportunity employer. All qualified applicants will be considered for employment without regard to their race, color, creed, religion, sex, pregnancy, national origin, ancestry, citizenship status, age, marital or partnership status, sexual orientation, gender identity or expression, disability, genetic predisposition, veteran or military status, status as a victim of domestic violence, a sex offense or stalking, or any other classification prohibited by applicable law.

As a registered investment adviser, employees of Hamilton Lane may be subject to certain limitations on political contribution and personal investment activities.

If you need a reasonable accommodation to complete your application, please contact Human Resources at humanresources@hamiltonlane.com.

Please note that in the event that you are hired by Hamilton Lane, you, your spouse or any other dependent family member living in your household will need to comply with Hamilton Lane's Personal Securities Transactions Policy and the trade pre-clearance process per Hamilton Lane's Code of Ethics. It is your responsibility to ensure that you and your household members are able to comply with this policy. Examples of the restrictions that could be placed on your activities include, but are not limited to, a requirement to pre-clear all transactions prior to execution, the inability to transact in certain securities or classes of securities and other restrictions. A copy of our Code of Ethics is available upon request. Please note that having a personal trading account will not prohibit you from being employed by Hamilton Lane.

As an employer who participates in the federal E-Verify program, Hamilton Lane will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS), with information from each employee’s Form I-9 to confirm work authorization. If the Government cannot confirm that you are authorized to work, the Company is required to provide you written instructions and an opportunity to contact SSA and/or DHS, so that you can resolve any discrepancies directly with the federal agency.

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